Abstract
Musical rhythm is shaped by both biological and cultural factors—nature and nurture. However, their relative contributions remain unclear, partly due to biased sampling. Traditional psychology experiments tend to recruit participants from a limited subset of the global population. To overcome this challenge, we use computational methods to analyze data gathered through both field and online research with diverse populations worldwide.
In this talk, I will present a decade-long research project dedicated to understanding cross-cultural rhythm representations. I will first introduce a paradigm I developed (Jacoby & McDermott, 2017) that reveals mental representations of rhythm (priors). In this paradigm, listeners reproduced random ‘seed’ rhythms; their reproductions were fed back as the stimulus (as in the game of ‘telephone’), such that their biases (the prior) could be estimated from the distribution of reproductions.
I will then describe a follow-up study that took nearly seven years to complete, in which we measured rhythmic priors across a diverse sample—923 participants from 39 participant groups across 15 countries and five continents, spanning both urban and indigenous societies. Our findings showed that integer ratio categories were universally present in rhythm, but their relative prominence varied across groups, often reflecting the structures of local musical traditions. Building on this, I will discuss follow-up studies exploring rhythm categorization in children and deaf individuals. Finally, I will highlight how rhythm research can now be conducted online using our online technology REPP (Anglada-Tort et al., 2022), enabling large-scale investigations into a wide range of phenomena—including the genetic basis of beat perception.
Bio
Nori Jacoby is an Assistant Professor at Cornell University and a Research Group Leader at the Max Planck Institute for Empirical Aesthetics in Frankfurt. His research explores the internal representations that shape sensory and cognitive abilities, examining how these representations are influenced by both innate biological factors and cultural experiences.To tackle these fundamental questions, he develops innovative methodologies, combining machine learning with behavioral experiments and scaling experimental research through large-scale online studies and global fieldwork. Nori earned his Ph.D. at the Edmond and Lily Safra Center for Brain Sciences (ELSC) at the Hebrew University of Jerusalem, under the supervision of Naftali Tishby and Merav Ahissar. He then pursued postdoctoral research at MIT in Josh McDermott’s Computational Audition Lab, at UC Berkeley in Tom Griffiths’s Computational Cognitive Science Lab, and as a Presidential Scholar in Society and Neuroscience at Columbia University.